[unreadable] Contemporary magnetic resonance imaging (MRI) methodology involves an implicit assumption, which is computationally convenient but physically inaccurate. This R21/R33 project seeks to develop a novel MRI methodology which abandons this assumption, thereby avoiding defects which commonly afflict rapid single-shot MR images. Because it interprets MRI raw data more accurately, the new methodology promises also to permit fundamentally more efficient, accurate and robust measurements to be made in several general types of MRI applications, such as diffusion imaging, measurement of tissue relaxation parameters, flow and motion imaging, and blood perfusion imaging. A strength of the general approach is that it measures tissue parameters more directly than do established approaches, which infer parameters from multiple separately acquired images. In an initial investigation and development of this methodology (termed PARSE), this project will implement a single-shot PARSE method, SS-PARSE, which is especially well-suited to functional MRI (fMRI) of the brain, with several theoretical advantages over existing methods used in fMRI. These theoretical advantages in accuracy, acquisition speed, and robustness, are substantiated in initial simulation trials. The immediate goal of the R21 project will be to experimentally verify these expected performance advantages of the SS-PARSE technique in well-controlled imaging studies using phantom objects in a 4.7T vertical-bore primate MR imaging system. A shortcoming of the methodology is that it requires much longer computation times than conventional MRI approaches. The R21 project will seek to develop much faster computational algorithms, and will determine the prospects for reducing computational time to roughly that of typical conventional fMRI studies. If these two major performance milestones have been met, the R33 project will commence, testing and characterizing the new methodology in functional brain imaging studies of primates. Additionally, the R33 project will include development of more sophisticated versions of the SS-PARSE method for high-resolution functional imaging. The project promises to introduce a new methodology, which may have substantial fundamental performance benefits over a broad range of clinical MRI applications. [unreadable] [unreadable]